by John on January 26, 2010
From Herbert Hoover, mining engineer and 31st President of the United States:
The great liability of the engineer compared to men of other professions is that his works are out in the open where all can see them. His acts, step by step, are in hard substance. He cannot bury his mistakes in the grave like the doctors. He cannot argue them into thin air or blame the judge like the lawyers. He cannot, like the architects, cover his failures with trees and vines. He cannot, like the politicians, screen his sort-comings by blaming his opponents and hope the people will forget. The engineer simply cannot deny he did it. If his works do not work, he is damned.

Related posts:
Architects versus engineers
Catalog engineering and reverse engineering
by John on January 11, 2010
by John on December 3, 2009
by John on November 30, 2009
“For a list of all the ways technology has failed to improve the quality of life, please press 3.” — Alice Kahn
by John on November 19, 2009
Here are three quotes on software development I ran across yesterday.
From Douglas Crockford, author of JavaScript, The Good Parts:
Just because something is a standard it doesn’t mean it’s the right choice for every application (e.g. XML).
From Yukihiro Matsumoto, creator of Ruby:
An open source project is like a shark. It must keep moving, or it will die.
From Roger Sessions, CTO of ObjectWatch:
A good IT architecture is made up largely of agreements to disagree. … Bad architectures and good both contain disagreements, but the bad architectures lack agreements on how to do so.
I once worked on a project that had a proprietary file format that became more sophisticated over time until it resembled a primitive relational database. After that I resolved to use standard technologies as much as possible. I think others have had the same experience and overreacted, using standard technologies even when they are overkill. Crockford’s comment is a reminder to moderate one’s zeal for standards. Moderation in all things.
I would add to Matsumoto’s comment that it’s not only open source projects that need to keep moving or die, though they may have an extra need for movement to maintain credibility.
The way I understand Sessions’ comment is that good architecture focuses on high level agreement rather than low-level conformity. “Let’s rewrite all our code in Java” is not a good software architecture. Or one that I hear more often “Let’s move everything to Oracle.” Such low-level standardization does not guarantee a coherently organized system. Whether subsystems use the same implementation technologies is not as important as whether there is a good strategy for making the pieces fit together.
Related posts:
Enterprise software
Million dollar software technique
JavaScript: A picture is worth a thousand words
by John on August 21, 2009
When you mix this quote from Author C. Clark
Any sufficiently advanced technology is indistinguishable from magic.
with Halnon’s Razor
Never attribute to malice that which can be adequately explained by stupidity.
you get Grey’s law
Any sufficiently advanced incompetence is indistinguishable from malice.
Update: Thanks to Wedge for leaving a comment identifying the last quote as Grey’s law.
From Orthodoxy by G. K. Chesterton:
The real trouble with this world of ours is not that is an unreasonable world, nor even that is a reasonable one. The commonest kind of trouble is that is nearly reasonable, but not quite. Life is not an illogicality; yet it is a trap for logicians. It looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait.
Isaac Newton famously said
If I have seen farther than others it is because I have stood on the shoulders of giants.
Later Mathematician R. W. Hamming added
Mathematicians stand on each other’s shoulders while computer scientists stand on each other’s toes.
Finally, computer scientist Hal Abelson quipped
If I have not seen farther, it is because giants were standing on my shoulders.
(Thanks to Mark Reid for the Hamming quote.)
by John on February 20, 2009
I just ran across a quote from Aristotle that seemed right in line with the quotes from John Tukey I posted the other day.
It is the mark of an educated man to look for precision in each class of things just so far as the nature of the subject admits.
I think Tukey and Aristotle may have gotten along well.
I believe Tukey said “There is no point in being precise when you don’t know what you’re talking about.” I’m going from memory, and that quote may not be verbatim. (I did a Google search on “john tukey quotes” and came up with maybe 20 pages that have the exact same three quotes from Tukey. I can’t imagine that 20 independent editors came up with the same three quotes. It’s not as if the man only said three memorable lines. I imagine there’s a great deal of copying going on.)
Here are a couple quotes from Tukey that Aristotle may have appreciated.
Finding the question is often more important than finding the answer.
The test of a good procedure is how well it works, not how well it is understood.
I have mixed feelings about the second quote. Sometimes you do have use things that work well even if you don’t understand why. For example, no one completely understands how anesthesia works. But Tukey was speaking in the context of statistical methods, and there I do see some virtue in using what you understand well even when something you don’t understand appears to work better. Maybe the poorly understood technique on appears to do better on a handful of examples and could fail on your data. But I believe Tukey was referring to techniques that many people have used successfully on a wide variety of problems even though the theoretical foundations haven’t been completely explored.
by John on February 18, 2009
Mark Reid sent me a link to a couple quotes by John Tukey that I had not seen before. First,
To statisticians, hubris should mean the kind of pride that fosters and inflated idea of one’s powers and thereby keeps one from being more than marginally helpful to others. … The feeling of “Give me (or more likely even, give my assistant) the data, and I will tell you what the real answer is!” is one we must all fight against again and again, and yet again.
Also,
The data may not contain the answer. The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
Here are some more posts about John Tukey:
Approximate problems and approximate solutions
Innovation IV
Tukey tallying
How to linearize data for regression
by John on February 18, 2009
From Mark Twain:
The secret of getting ahead is getting started. The secret of getting started is breaking your complex and overwhelming tasks into small manageable tasks, and then starting on the first one.
by John on October 31, 2008
Signal vs Noise had this quote from Warren Buffet.
One thing to remember in economics is that you can’t do one thing in economics. There are always other effects that come out of it.
As I’ve heard someone say, the first step in learning to think like an economist is to ask “And then what?”
Here’s a quote from a recent blog post from Tom Peters:
You will be remembered in the long haul for the quality of your work, not the quantity of your work—the quantity part is just your defective ego talking—no one evaluates Picasso based on the number of paintings he churned out.
Greg Wilson pointed out an article in The Chronicle of Higher Education about scientists using Photoshop to manipulate the graphs of their results. The article has this to say about The Journal of Cell Biology.
So far the journal’s editors have identified 250 papers with questionable figures. Out of those, 25 were rejected because the editors determined the alterations affected the data’s interpretation.
This immediately raises suspicions of fraud which is, of course. However, I’m more concerned about carelessness than fraud. As Goethe once said,
…misunderstandings and neglect create more confusion in this world than trickery and malice. At any rate, the last two are certainly much less frequent.
Even if researchers had innocent motivations for manipulating their graphs, they’ve made it impossible for someone else to reproduce their results and have cast doubts on their integrity.